Modern inventory systems, such as those in mail order warehouses, supply chain distribution centers, airport luggage systems, and custom-order manufacturing facilities, face significant challenges tracking items held in inventory. As items are moved around, for example, within a mail order warehouse, the probability that the item will be lost or misplaced is increased. This presents a problem for the warehouse operator as the item may not be discoverable when needed (e.g., when the item is needed to fulfill an order). Accordingly, it may be desirable to track items as they are moved within the warehouse. Currently, motion detecting and tracking techniques may include the use of still or motion picture cameras in conjunction with image recognition techniques. However, these techniques provide a number of disadvantages. For example, the expense of the equipment needed alone (e.g., video cameras, systems to analyze the images) may be cost prohibitive to implement. Additionally, analyzing large amounts of images may require extensive computing power. Further, utilizing image recognition techniques for tracking objects in three-dimensional space may prove inaccurate in some circumstances, such as in environments with many fast-moving objects.
Other techniques for determining a location of an item may utilize Light Detection And Ranging (LIDAR) techniques. Such techniques measure distance to an object by illuminating a target with a laser light signal and calculating distances by measuring the time for the signal to return. These techniques, however, are susceptible to inaccuracy if the object surface absorbs a broad range of the light spectrum as would be the case with an object that was covered in black felt. Similarly, inaccuracies would occur if the object surface is too reflective, as would be the case with an object with a mirror-like surface.